fix noisy_peak signature in example-notebook.ipynb

Author: basnijholt

example-notebook.ipynb

@@ -104,7 +104,7 @@
    "source": [
     "# The end condition is when the \"loss\" is less than 0.01. In the context of the\n",
     "# 1D learner this means that we will resolve features in 'func' with width 0.01 or wider.\n",
-    "runner = adaptive.Runner(learner, goal=lambda l: l.loss() < 0.01, tasks=4)\n",
+    "runner = adaptive.Runner(learner, goal=lambda l: l.loss() < 0.01)\n",
     "runner.live_info()"
    ]
   },
@@ -312,9 +312,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def noisy_peak(x, sigma=0, peak_width=0.05, offset=-0.5):\n",
+    "def noisy_peak(seed_x, sigma=0, peak_width=0.05, offset=-0.5):\n",
+    "    seed, x = seed_x\n",
     "    y = x ** 3 - x + 3 * peak_width ** 2 / (peak_width ** 2 + (x - offset) ** 2)\n",
-    "    noise = np.random.normal(0, sigma)\n",
+    "    rng = np.random.RandomState(int(seed))\n",
+    "    noise = rng.normal(scale=sigma)\n",
     "    return y + noise"
    ]
   },
@@ -332,7 +334,7 @@
    "outputs": [],
    "source": [
     "xs = np.linspace(-2, 2, 500)\n",
-    "ys = noisy_peak(xs, sigma=0)\n",
+    "ys = [noisy_peak((seed, x), sigma=0) for seed, x in enumerate(xs)]\n",
     "hv.Path((xs, ys))"
    ]
   },
@@ -349,7 +351,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ys = [noisy_peak(x, sigma=1) for x in xs]\n",
+    "ys = [noisy_peak((seed, x), sigma=1) for seed, x in enumerate(xs)]\n",
     "hv.Path((xs, ys))"
    ]
   },